Adaptive Learning Environment Research Articles

Understanding Clinical Learning Quality Aspects in Mental Health Nursing Practice Course among Students: A Comprehensive Examination

There is a growing demand for comprehensive evaluations of the clinical learning quality of nursing education and the necessity to establish robust predictors and mediators for enhancing its outcomes within the context of mental health practice. This study is threefold: 1. Evaluating nursing students’ clinical learning quality before and after mental health nursing practice; 2. Establish if the grade of a theoretical course in mental health nursing and the student’s perception of their theoretical knowledge level predicts the grade of mental health nursing practice; 3. Explore how model learning opportunities, self-directed learning, safety, and nursing care quality mediate learning environment quality and tutorial strategies quality following mental health nursing practice. Using a before and after the study, 107 undergraduate nursing students at an Israeli university completed a questionnaire and the Clinical Learning Quality Evaluation Index tool to assess their perceptions of clinical learning quality before and after mental health nursing practice. The results showed a decline in students’ perceptions of tutorial strategy quality following mental health practical learning in clinical settings, with the theoretical course grade predicting the practical experience grade and underscoring the mediating role of learning opportunities between the learning environment and tutorial strategies. The study’s findings emphasize the importance of an adaptive learning environment and a solid theoretical foundation in fostering effective tutorial strategies and enhancing the overall learning outcomes for nursing students in mental health education.

Project VoLL-KI

Abstract“Learning from Learners” (“Von Lernenden Lernen”, “VoLL-KI ” for short) is a is collaborative research project with the goal of creating a practical toolbox of instruments at different levels of abstraction to improve the learning experience and outcomes for students of artificial intelligence. Learning and teaching at tertiary education institutions are currently IT-based but not AI-supported. The VoLL-KI project aims to go this crucial next step. Using AI approaches (e.g., ML, symbolic AI, statistical AI), several educational technologies are developed on the different granularity of the study programs (e.g., course, semester, program). So, dashboards for study planning, recommender systems improving student advisory services and learning material selection, VR-based learning experiences, educational chatbots, and adaptive learning environments are developed. The systems are mostly deployed as prototypes

УПРОВАДЖЕННЯ СИСТЕМ УПРАВЛІННЯ НАВЧАННЯМ З ФУНКЦІЯМИ ГЕНЕРАТИВНОГО ШТУЧНОГО ІНТЕЛЕКТУ В УМОВАХ ПОСТ-ПАНДЕМІЇ

In recent years, the global education system has undergone a transformative shift, relying increasingly on online tools to prove its resilience in the face of various challenges, including epidemiological events. This paper seeks to introduce a Learning Management System (LMS) designed to elevate the delivery of educational content, fostering the training and development of students' knowledge in a dynamic and adaptive learning environment anchored to the connectivity and synchronization needs of smart urban living. The system proposes the integration of a language generation model equipped with Application Programming Interface (API) access. This choice not only streamlines instructor support but also facilitates the creation of courses using an adapted and coherent language. The system goes beyond traditional LMS functionalities by providing suggestions to enhance and diversify lessons. Emphasizing flexibility and adaptability, the proposed LMS caters to various training levels, being able to accommodate the needs of learners across different domains. To identify the appropriate solution, a comparative analysis was conducted, evaluating various platforms based on functionality, intuitive presentation, and customization options. The selected system emerged as the most favorable, offering a robust framework for the development and delivery of educational content. To demonstrate the system's effectiveness, a curriculum was crafted for a specialized field of study - Artificial Intelligence (AI), with a specific focus on the practical application of Machine Learning algorithms. This curriculum incorporates theoretical and practical application components, complemented by a suite of assessment tools and assignments tailored to the proposed subject. The lessons within this curriculum were constructed by drawing insights from various bibliographical sources. What sets this system up-to-date is its integration of generative AI features directly into the LMS, enriching the teaching-learning-evaluating experience.

Self‐regulation and shared regulation in collaborative learning in adaptive digital learning environments: A systematic review of empirical studies

AbstractAdaptive learning technologies are closely related to learners' self‐regulatory processes in individual and collaborative learning. This study presents the outcomes of a systematic literature review of empirical evidence on adaptive learning environments to foster self‐regulation and shared regulation of learning in collaborative settings. We provide an overview of what and how adaptive technologies have been used to understand and promote self‐regulated learning in collaborative contexts. A search resulted in 38 papers being analysed. Specifically, we identified the seven main objectives (feedback and scaffolding, self‐regulatory skills and strategies, learning trajectories, collaborative learning processes, adaptation and regulation, self‐assessment, and help‐seeking behaviour) that the adaptive technology research has been focusing on. We also summarize the implications derived from the reviewed papers and frame them within seven thematic areas. Finally, this review stresses that future research should consider developing a converging theoretical framework that would enable concrete monitoring and support for self‐regulation and socially shared regulation of learning. Our findings set a baseline to support the adoption and proliferation of adaptive learning technology within self‐regulated learning research and development. Practitioner notesWhat is already known about this topic By providing personalized and learner‐centric adaptive learning environments (ADLEs), adaptive learning technology can support and foster self‐regulated learning (SRL) practices. It is possible to create a more student‐centred and effective learning environment by combining adaptive learning and collaborative learning. Socially shared regulatory activities can involve planning, monitoring, controlling and reflecting on a group's learning processes. What this paper adds Provides a systematic literature review of empirical evidence on ADLEs, SRL and socially shared regulation of learning (SSRL) in collaborative contexts. Summarizes the insights on (S)SRL through ADLEs in collaborative learning. Identifies challenges and opportunities for ADLEs to support (S)SRL in collaborative learning. Implications for practice and/or policy Learning analytics and educational technology researchers will be able to use the systematic review as a guide for future research. Learning analytics and educational technology practitioners will be able to use the systematic review as a summary of the field's current state.

Investigating popular topics for the integration of the internet of things in physical education: A content analysis in higher education

Background Problems: Advanced technologies, such as the Internet of Things (IoT), have played an increasingly important role in the development of physical education in higher education. Research Objectives: This study aims to conduct a content analysis of the use of IoT technology in physical education in higher education. Methods: Scopus and Web of Science databases were used to collect and analyse data for this study, with a total of 178 articles obtained, consisting of 104 articles (Scopus) and 74 articles (Web of Science). The final data used for this study consisted of 20 articles, as it only targeted the top five topics related to the internet of things (IoT) in physical education after being analysed using ScientoPy. Findings and Results: The analysis identified five main topics related to the application of the internet of things in physical education in higher education, including cloud, artificial intelligence, deep learning, big data, and virtual reality. The implications of these findings for the development of physical education in higher education are discussed in this study, emphasizing the importance of IoT technology integration in creating a more adaptive and responsive learning environment. Conclusion: The contributions of this research include providing deeper insights into how IoT technologies can be applied in physical education in higher education, as well as highlighting the potential to improve the effectiveness of learning and teaching in this area. The conclusions of this study emphasises the importance of continuing to develop innovations in the application of IoT technology in physical education in higher education in order to achieve a more efficient and competitive learning environment.

GRAMMAROUS Revolutionizing English Vocabulary Acquisition for Children through Gamified Learning

Interactive Learning through Gamified Activities: The Grammarous App This paper presents Grammarous, a novel Android application that revolutionizes children's English vocabulary acquisition through interactive and gamified activities. By leveraging cutting-edge technologies and principles of gamification, Grammarous incorporates a diverse range of engaging features tailored to cater to various learning styles, making vocabulary acquisition an enjoyable and highly effective process for young learners. The app employs innovative techniques such as Shake-to-Spell, where children can rearrange scrambled letters into words by shaking their devices, fostering both visual and kinesthetic learning. Other features include Fill-in-the-blanks to reinforce memory and spelling, Spelling Bees for friendly competition, Rearrange Words to stimulate critical thinking, Matching Games for solidifying vocabulary relationships, and Shake Alphabets for letter recognition and mastery. Grammarous leverages Firebase Authentication for secure user management and real-time data retrieval to facilitate personalized learning experiences. By seamlessly integrating education and technology, the app creates an immersive and adaptive learning environment that actively engages children and promotes cognitive development. With its innovative approach to gamifying language learning, Grammarous has the potential to revolutionize the field of educational technology, providing a fun and effective platform for children to acquire essential English vocabulary skills crucial for academic and personal growth. Keywords: android app, vocabulary, gamification, spelling bee, innovative, educational games, language expansion, interactive learning, cognitive development, personalized education

Adaptive Learning is Hard: Challenges, Nuances, and Trade-offs in Modeling

AbstractWhile the potential of personalized education has long been emphasized, the practical adoption of adaptive learning environments has been relatively slow. Discussion about underlying reasons for this disparity often centers on factors such as usability, the role of teachers, or privacy concerns. Although these considerations are important, I argue that a key factor contributing to this relatively slow progress is the inherent complexity of developing adaptive learning environments. I focus specifically on the modeling techniques that provide the foundation for adaptive behavior. The design of these models presents us with numerous challenges, nuances, and trade-offs. Awareness of these challenges is essential for guiding our efforts, both in the practical development of our systems and in our research endeavors.

Reframing A Self-Organized Learning Environment (SOLE) to Accommodate Indonesian EFL Students’ Learning Loss

In the wake of the COVID-19 lockdown, students have faced heightened learning loss, attributed to factors such as inadequate learning methods, restricted access to education, decreased instructional time, and emotional stressors. Particularly affected is English language learning, prompting the need for effective remedies. This study proposes the implementation of new Self-Organized Learning Environments (SOLEs) as a strategic response to mitigate learning setbacks, especially in post-pandemic contexts. Employing a systematic review of relevant literature and employing established methodologies for position paper composition, this research undertakes a comprehensive analysis of SOLEs' effectiveness in nurturing students who experienced learning loss. Divided into three focal areas, the study explores the evolving new role of teachers within SOLEs, the integration of SOLEs in English as a Foreign Language (EFL) pedagogy, and the utilization of digital applications to enhance language-focused SOLE practices. Through this multifaceted analysis, the study aims to offer innovative insights and actionable recommendations for addressing learning loss and fostering resilient educational strategies in the aftermath of the pandemic.The results of this study contribute valuable knowledge to the ongoing discourse on educational recovery, with implications for educators, policymakers, and stakeholders invested in creating adaptive and effective learning environments.

Building paths to success: a multilevel analysis of the effects of an emotional intelligence development program on the academic achievement of future teachers.

The situation generated by the recent pandemic has had several effects on education, one of them being the necessary but hasty efforts of teachers and students to adapt to the demands of a virtual classroom environment. Thus, it is essential to promote the development of digital competencies in future teachers, enabling them to create effective learning situations in the digital medium. Moreover, the European university curriculum includes a set of specific competencies (specific to each degree) and a series of generic competencies, many of which are related to emotional intelligence. Our work emerges from these specific premises and the more general need to develop emotional skills and learning abilities in virtual environments for future educators. The sample comprised 240 students in higher education, pursuing a bachelor's degree in education at the University of Alicante, Spain (68.3% were female and average age of the participants was 19.43 years SD = 4.127). Using a quasi-experimental design with pretests, posttests, and a control group, we present the effects of an online program aimed at improving the emotional skills and academic achievement of future teachers in higher education. In this study, a 30-h emotional intelligence training program was implemented. Since the student sample was grouped into different classes, we analyzed, using a generalized linear mixed-effects model, whether students who took the program showed a significant improvement in their academic achievement at the end of their studies, compared to those who did not take it. The findings show a significant improvement in the academic achievement at the end of the bachelor's degree studies of the students in the experimental group. These results open up a field of possibilities for the implementation of this type of training using virtual environments, enabling interventions to enhance the emotional development of the teaching staff (and, subsequently, in their students), develop their teaching careers adequately, and employ the ideal strategies to address educational programs. Looking ahead, the integration of emotional development programs that incorporate emerging technology into university curricula could enhance the preparation of educators profoundly and create adaptable learning environments for contemporary students.

Integrating emerging technologies into classrooms: a multimedia perspective

This research aimed to understand how emerging technologies are transforming pedagogical practices in education. The main objective was to analyze the adoption of technologies such as augmented reality, artificial intelligence, and mobile learning in classrooms, assessing their impact on student engagement and motivation. The methodology was based on a literature review, following Gil's guidelines (2002), allowing for a comprehensive analysis of recent studies on the subject. The results showed a significant impact of emerging technologies on education, offering opportunities for more engaging and adaptive learning environments, as discussed by authors like Freitas (2017) and Alves and Nogueira (2019). However, challenges such as resistance to change, resource limitations, and the need for continuous teacher training were identified. The final considerations highlighted the importance of emerging technologies as transformative elements in education, despite the existing challenges. This study emphasizes the need to overcome these obstacles to maximize the benefits of technological innovations in education.

A Novel Neural Ensemble Architecture for On-the-fly Classification of Evolving Text Streams

We study on-the-fly classification of evolving text streams in which the relation between the input data and target labels changes over time—i.e., “concept drift.” These variations decrease the model’s performance, as predictions become less accurate over time and they necessitate a more adaptable system. While most studies focus on concept drift detection and handling with ensemble approaches, the application of neural models in this area is relatively less studied. We introduce Adaptive Neural Ensemble Network ( AdaNEN ), a novel ensemble-based neural approach, capable of handling concept drift in data streams. With our novel architecture, we address some of the problems neural models face when exploited for online adaptive learning environments. Most current studies address concept drift detection and handling in numerical streams, and the evolving text stream classification remains relatively unexplored. We hypothesize that the lack of public and large-scale experimental data could be one reason. To this end, we propose a method based on an existing approach for generating evolving text streams by introducing various types of concept drifts to real-world text datasets. We provide an extensive evaluation of our proposed approach using 12 state-of-the-art baselines and 13 datasets. We first evaluate concept drift handling capability of AdaNEN and the baseline models on evolving numerical streams; this aims to demonstrate the concept drift handling capabilities of our method on a general spectrum and motivate its use in evolving text streams. The models are then evaluated in evolving text stream classification. Our experimental results show that AdaNEN consistently outperforms the existing approaches in terms of predictive performance with conservative efficiency.

Artificial intelligence for human learning: A review of machine learning techniques used in education research and a suggestion of a learning design model

The goal of this research is to (1) identify the status and development of AI and ML-based learning support systems and their impact on human learning, with a specific focus on techniques employed in previous research, and (2) demonstrate the process of designing a learning support system using AI. Artificial intelligence (AI) and machine learning (ML) technologies have received attention in education. The existing research on AI in education is examined, considering the implications of its application in research. Noteworthy ML techniques from the literature are explained, followed by a discussion on leveraging AI and ML technologies to enhance learning support. Additionally, with consideration of both front-end and back-end approaches,a framework for incorporating AI into education is proposed. Subsequently, a learning design model, Self-regulated Learning with AI Assistants (SLAA), is suggested for addressing the objectives of AI-based learning support system design. The categorization of AI and ML techniques in education research reveals nine types, including supervised learning, mining approaches, and Bayesian techniques. The exploration illustrates how these techniques can be employed in designing a learning support system. This paper provides an empirical overview of AI in education, addresses technological and pedagogical considerations for developing personalized and adaptive learning environments, and outlines the challenges and potential future research directions.

Addressing complexity in motor learning: Practical strategies for teachers and coaches

This research embarks on an exploration delving into the intricacies of motor skill acquisition and its versatile application across various contexts. Its core objective resides in fostering a robust discourse within this domain. Emphasizing the qualitative dimension of mastering motor skills underscores an urgent need for evidence-backed teaching methodologies that boast universal applicability. In the realms of physical education and sports, a profound comprehension of fundamental theoretical frameworks stands as a pivotal requirement to facilitate effective pedagogy. The continuous evolution of innovative teaching approaches within motor and sports education accentuates the necessity for a meticulous examination of the foundational theoretical underpinnings supporting these advancements. The principal aim of this investigation primarily revolves around distilling the fundamental principles embedded within the ecological-dynamic approach to learning. Furthermore, it endeavors to illuminate actionable directives tailored for instructional purposes. These directives aspire to cultivate adaptive learning environments conducive to the acquisition of motor and sports skills, prioritizing flexibility over rigidity and nurturing an environment that encourages perpetual learning experiences. To achieve this ambitious goal, an exhaustive scrutiny of recent literature has been undertaken, placing significant emphasis on notable contributions propelling the ongoing discourse forward. This comprehensive review endeavors to enrich the dialogue surrounding evidence-based teaching methodologies within the realm of motor skill acquisition and sports education.

Bridging the gap: Using robotics to enhance emotional and social learning in K-12 education

This research explores the integration of robotics into K-12 education to enhance emotional and social learning (ESL). The theoretical framework draws from constructivism, social learning theory, experiential learning, socio-cultural theory, and emotional intelligence models. Implementation strategies include curriculum design, teacher training, student engagement, and ethical considerations. Challenges encompass ethical dilemmas, access disparities, and socio-cultural sensitivity. The future of robotics in education involves technological advances, global collaboration, and adaptive learning environments. The conclusion emphasizes the transformative potential of robotics in cultivating well-rounded individuals with technical proficiency and heightened socio-emotional skills. As the educational landscape evolves, the integration of robotics emerges as a dynamic force shaping a generation prepared for the complexities of the 21st century.

Motivating Students to Learn Mathematics in the iGrowMaths Classroom: An Innovative Adaptive Classroom in Business Mathematics Education

The COVID-19 pandemic has exacerbated the inequalities in educational attainment and achievement, especially for students from disadvantaged socio-economic backgrounds. The teaching and learning process has become more complex as students are increasingly diverse in terms of prior knowledge and learning pace. Hence, this study proposes and designs the iGrowMaths Classroom, an innovative adaptive learning classroom for Business Mathematics course at a public polytechnic in Malaysia. The purpose is to create an adaptive learning environment that builds on the level of prior knowledge and learning pace in order to promote motivation and improve achievements in mathematics. The case study design was employed to investigate the effectiveness of iGrowMaths Classroom, with the adoption of a triangulation method that involved questionnaires, interviews, and formative assessment. The findings reveal that the iGrowMaths classroom is effective in fostering the students’ motivation towards learning mathematics and thereby enhancing the learning outcomes.

Optimizing marketing learning evaluation: Gamification with CIPP model at SMKN 1 Bandung

In this digital era, education is experiencing rapid growth, especially in the diversity of evaluations given to students, one of which is through gamification. This article explores optimizing learning evaluation through gamification in the CIPP (Context, Input, Process, Product) evaluation model in marketing education at SMKN 1 Bandung. The method used is descriptive quantitative research. Data collection is done through questionnaires and interviews. The data sources and subjects in this study are educators in the marketing subject at SMKN 1 Bandung and students majoring in Online Business and Marketing at SMKN 1 Bandung, with the object being the evaluation of marketing learning with the implementation of gamification in the CIPP model. The results of this study indicate that the learning evaluation process with gamification is well-received by students at SMKN 1 Bandung. Applying gamification in learning evaluation using the CIPP model enhances students' learning outcomes and creates a responsive, adaptive, and collaborative learning environment.

Educational Management Innovation by Utilizing Artificial Intelligence in Higher Education

Innovation in higher education is essential to align teaching with technological developments. The use of artificial intelligence (AI) offers great potential to improve education management in higher education through optimizing the teaching and learning process. This research aims to explore how the integration of artificial intelligence in education management can improve the efficiency, effectiveness, and quality of students' learning experience in higher education. The research method includes a comparative analysis between conventional education management systems and systems that utilize artificial intelligence, as well as the implementation of AI technology in the decision-making process in higher education. The results show that the application of artificial intelligence can improve the ability of prediction, data analysis, adaptation, and personalization in curriculum management, student performance evaluation, and the provision of learning resources tailored to individual needs. Artificial intelligence in education management in higher education has opened up various opportunities. Artificial intelligence enables personalization of learning. In addition, the use of artificial intelligence in administration has also improved the efficiency of resource management and administrative processes. The conclusion of this study states that the utilization of artificial intelligence in educational management in higher education can bring about positive changes. By effectively utilizing artificial intelligence technology, universities can improve students' learning experience and optimize administrative efficiency, better preparing students for future challenges. It can also manage education in higher education to create a more adaptive, responsive, and innovative learning environment, which in turn can improve the overall quality of higher education.

THE FOUR C’S OF TEACHING OLDER LEARNERS: IMPLICATIONS FOR THE WORKPLACE AND CAREER WORK–LIFE EXTENSION EFFORTS

Abstract From Spring 2017 through Spring 2022, a sample of older (age 40 and above) undergraduate and graduate students who were also first-time online students (n = 86) from a very diverse student population at Northeastern Illinois University were analyzed on various motivational and performance indices regarding fully online course performance (e.g., student expectations, receptivity to on-line modules, time management skills). A comparative analysis of the two student samples yielded some interesting “universal” course design issues across education levels, as well as by cultural background and gender differences. Specific fully online design issues to be discussed as are how to create the clearest “face-to-face” representation of the classroom experience via a course learning management system. Effective design issues will be discussed in creating a supportive, fully online course environment for older online course students. General design issues to be discussed are how to create a well-structured “face-to-face” representation of the classroom experience for a diverse older student population with equally diverse learning needs/issues, a supportive fully online learning environment for “first-time” online course students, and tailored, adaptive learning environment to meet the dynamic needs of students (undergraduate, graduate) over the progress of an e-course. The presentation will present and discuss the four C’s in promoting a positive and enriched learning environment for diverse “non-traditional” adult learners faced with online learning in different contexts with implications for learning in the workplace for adaptive career work-life extension.

The Future of Education: Exploring AI Avatars in Higher Learning

This article explores the integration of AI avatars in higher learning, analyzing their potential to revolutionize education. AI avatars, virtual entities equipped with advanced algorithms, personalize learning experiences, enhance student engagement, and address diverse needs. Despite benefits, challenges such as ethical considerations and data privacy exist. Case studies illustrate successful implementations, showcasing the transformative impact. The integration process is outlined systematically, providing a roadmap for institutions. Overall, this exploration reveals the potential of AI avatars to redefine education, creating an adaptive, engaging, and inclusive learning environment. Embracing benefits, addressing challenges, and following a strategic process are key for this transformative future.

Pemanfaatan Tranformasi Digital Untuk Mendukung Proses Pembelajaran Siswa-Siswi SMA-IT Atta’awun Sukaresmi

In the modern era, digital transformation has changed nearly every aspect of our lives, and education is no exception. The advancements in information and communication technology have had a significant impact on how we learn, teach, and interact within the context of education. The utilization of digital transformation in the world of education is becoming increasingly important as it holds the potential to enhance the quality of learning and create a more inclusive, interactive, and adaptive learning environment, as seen at Attaawun Sukaresmi High School. The aim of this research is to understand how students effectively utilize digital media. This study will employ a qualitative approach with a case study method. Data will be gathered through interviews with various stakeholders at Attaawun Sukaresmi High School, including teachers and students. Additionally, an analysis of the utilization of digital media at the school will be conducted. The results of this research are expected to provide a deeper understanding of the use of digital media such as smartphones, laptops, and others. Furthermore, concrete strategies and steps will be proposed that can be taken by the government, institutions, or schools to optimize the positive use of digital media. Thus, Attaawun High School can serve as an example for other schools in coping with the changing times due to the development of digital technology.